<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In recent years, mapping of knowledge domain and political knowledge has developed rapidly and gradually penetrated into many practical applications. The construction of an ideological and political knowledge framework for colleges has become one of the important applications. Therefore, commencing with the theory of mapping of knowledge domain, and aiming at resolving the difficulty involved in effectively extracting and analysing ideological and political knowledge, a mining method for ideological and political knowledge elements is constructed in this paper, based on LDA model and Apriori algorithm. By setting a three-dimensional matrix of keywords and association rules, an algorithm for mining of ideological and political knowledge elements is proposed, where LDA model is used to acquire ideological and political subject words, and Apriori algorithm is used to discover tacit ideological and political knowledge. It is helpful to solve the problem of excavation and presentation of ideological and political elements in college curriculum, serve the ideological and political construction of curriculum, which is of great significance to dredge students’ learning paths and reduce learners’ learning cost.</p>
</abstract>

In recent years, mapping of knowledge domain and political knowledge has developed rapidly and gradually penetrated into many practical applications. The construction of an ideological and political knowledge framework for colleges has become one of the important applications. Therefore, commencing with the theory of mapping of knowledge domain, and aiming at resolving the difficulty involved in effectively extracting and analysing ideological and political knowledge, a mining method for ideological and political knowledge elements is constructed in this paper, based on LDA model and Apriori algorithm. By setting a three-dimensional matrix of keywords and association rules, an algorithm for mining of ideological and political knowledge elements is proposed, where LDA model is used to acquire ideological and political subject words, and Apriori algorithm is used to discover tacit ideological and political knowledge. It is helpful to solve the problem of excavation and presentation of ideological and political elements in college curriculum, serve the ideological and political construction of curriculum, which is of great significance to dredge students’ learning paths and reduce learners’ learning cost.

Research on the mining of ideological and political knowledge elements in college courses based on the combination of LDA model and Apriori algorithm

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In recent years, mapping of knowledge domain and political knowledge has developed rapidly and gradually penetrated into many practical applications. The...

Research on the mining of ideological and political knowledge elements in college courses based on the combination of LDA model and Apriori algorithm

Publicado en línea: 20 may 2022

Páginas: 2345 - 2356

Recibido: 22 mar 2022

Aceptado: 10 abr 2022

DOI: https://doi.org/10.2478/amns.2021.2.00190

Palabras clave
Mapping of knowledge domain, LDA model, Apriori algorithm, Ideological and political knowledge element

© 2023 Long Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

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Research on the mining of ideological and political knowledge elements in college courses based on the combination of LDA model and Apriori algorithm

Publicado en línea: 20 may 2022

Páginas: 2345 - 2356

Recibido: 22 mar 2022

Aceptado: 10 abr 2022

DOI: https://doi.org/10.2478/amns.2021.2.00190

Palabras claveMapping of knowledge domain, LDA model, Apriori algorithm, Ideological and political knowledge element

© 2023 Long Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Palabras clave
Mapping of knowledge domain, LDA model, Apriori algorithm, Ideological and political knowledge element